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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Analytics and Business Community | - |
| dc.date.accessioned | 2021-05-16T06:17:19Z | - |
| dc.date.available | 2021-05-16T06:17:19Z | - |
| dc.date.issued | 2019 | - |
| dc.identifier.uri | http://172.21.1.51:8080/xmlui/handle/123456789/1758 | - |
| dc.description.abstract | Give yourself a pat on the back for crossing the first milestone in this interesting journey of analytics and data science. Now that you have your basics clear, it’s time that we delve deeper into the nuances of another crucial part in data science: Numpy & Pandas, your two evergreen friends in this journey. Both these libraries are of extreme importance from your placement as well as research point of view. In fact, logic developed while studying these two libraries is used in various other languages like SQL as well. | en_US |
| dc.language.iso | en | en_US |
| dc.subject | Python | en_US |
| dc.subject | Summer Analytics | en_US |
| dc.subject | Data Analytics | en_US |
| dc.title | MODULE 02: NUMPY AND PANDAS | en_US |
| dc.type | Technical Report | en_US |
| Appears in Collections: | Business Analytics | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| MODULE 02- Numpy and Pandas.pdf | 131.13 kB | Adobe PDF | View/Open |
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